R Notebook

library(readxl)
library(tidyverse)

sep07 <- read.csv("../data/clean_data/npoc_7sep21.csv")%>%
  mutate(Day = as.Date("2021-09-07"))
sep08 <- read.csv("../data/clean_data/npoc_8sep21.csv")%>%
  mutate(Day = as.Date("2021-09-08"))
sep09 <- read.csv("../data/clean_data/npoc_9sep21.csv")%>%
  mutate(Day = as.Date("2021-09-09"))
sep14 <- read.csv("../data/clean_data/npoc_14sep21.csv")%>%
  mutate(Day = as.Date("2021-09-14"))
sep15 <- read.csv("../data/clean_data/npoc_15sep21.csv")%>%
  mutate(Day = as.Date("2021-09-15"))
sep16 <- read.csv("../data/clean_data/npoc_16sep21.csv")%>%
  mutate(Day = as.Date("2021-09-16"))
sep17 <- read.csv("../data/clean_data/npoc_17sep21.csv")%>%
  mutate(Day = as.Date("2021-09-17"))
sep20 <- read.csv("../data/clean_data/npoc_20sep21.csv")%>%
  mutate(Day = as.Date("2021-09-20"))
sep21 <- read.csv("../data/clean_data/npoc_21sep21.csv")%>%
  mutate(Day = as.Date("2021-09-21"))

full = sep07%>%
  full_join(sep08)%>%
  full_join(sep09)%>%
  full_join(sep14)%>%
  full_join(sep15)%>%
  full_join(sep16)%>%
  full_join(sep17)%>%
  full_join(sep20)%>%
  full_join(sep21)%>%
  filter(!grepl("spk|dup",Sample))

Joining, by = c("Sample", "NPOC", "TNb", "Day")
Joining, by = c("Sample", "NPOC", "TNb", "Day")
Joining, by = c("Sample", "NPOC", "TNb", "Day")
Joining, by = c("Sample", "NPOC", "TNb", "Day")
Joining, by = c("Sample", "NPOC", "TNb", "Day")
Joining, by = c("Sample", "NPOC", "TNb", "Day")
Joining, by = c("Sample", "NPOC", "TNb", "Day")
Joining, by = c("Sample", "NPOC", "TNb", "Day")

full$Sample_day <- as.numeric(sub("[a-z]+[0-9]+d","",sub("([a-z](_.+)*$)","",full$Sample)))
full$Rep <- as.numeric(substr(full$Sample,4,4))
full$filt <- sub("[a-z]+[0-9]+[a-z]+[0-9]+","",sub("_.+","",full$Sample))
full$Treatment <- substr(full$Sample,1,2)
full_conc = full

full_conc$Treatment[full_conc$Treatment=="aa"]<-"Anoxic"
full_conc$Treatment[full_conc$Treatment=="oo"]<-"Oxic"
full_conc$Treatment[full_conc$Treatment=="oa"]<-"Oxic to anoxic"
full_conc$Treatment[full_conc$Treatment=="ao"]<-"Anoxic to oxic"

fer = full_conc
fer$filt[fer$filt=="s"]<-"Filtered"
fer$filt[fer$filt=="t"]<-"Unfiltered"

fer$Status <- "Oxic"
fer$Status[fer$Treatment %in%c("Anoxic to oxic","Anoxic")]<- "Anoxic"

write.csv(fer,"../data/processed_data/TOC_formatted.csv", row.names = F)

full_conc$Treatment[full_conc$Treatment=="Anoxic to oxic"&full_conc$Sample_day<=13]<-"Anoxic"
full_conc$Treatment[full_conc$Treatment=="Oxic to anoxic"&full_conc$Sample_day<=13]<-"Oxic"

f = fer%>%
  filter(!is.na(Treatment))%>%
  ggplot(aes(x = Sample_day, y = NPOC, color = Treatment))+
  geom_point()+
  ylab("NPOC (mg/L)")+
  geom_vline(xintercept = 13.5)+
  scale_color_manual(values = c("#175676","#D58936","#A44200","#4BA3C3")) +
  facet_grid(Status~filt)+
  theme_bw()

fer%>%
  filter(!is.na(Treatment))%>%
  ggplot(aes(x = Sample_day, y = TNb, color = Treatment))+
  geom_point()+
  ylab("Total bound nitrogen (mg/L)")+
  xlab("Day of experiment")+
  geom_vline(xintercept = 13.5)+
  scale_color_manual(values = c("#175676","#D58936","#A44200","#4BA3C3")) +
  facet_grid(Status~filt)+
  theme_bw()

library(plotly)
ggplotly(f)

fer%>%
  filter(Sample_day == 9,
         filt == "Filtered",
         Treatment == "Oxic")

fer

f